Compositions and methods for determining receptivity of an endometrium for embryonic implantation

ABSTRACT

Provided herein are methods and kits for determining receptivity status of an endometrium for embryonic implantation.

CLAIM OF PRIORITY

This application claims the benefit of U.S. Provisional PatentApplication Ser. No. 62/453,631, filed on Feb. 2, 2017. The entirecontents of the foregoing are hereby incorporated by reference.

TECHNICAL FIELD

The present disclosure relates generally to the fields of reproductivemedicine. More specifically, this disclosure relates to in vitro methodsand kits for determining the receptivity status of an endometrium forembryonic implantation.

BACKGROUND

The endometrium reaches a receptive status for embryonic implantationaround day 19-21 of the menstrual cycle. The number of moleculardiagnostic tools available to characterize the receptive status forembryonic implantation is very limited and lack key elements for theaccurate determination of the window of implantation (WOI), such asimmune response genes, crucial for embryo implantation.

SUMMARY

In one aspect, the disclosure provides methods of predicting endometrialreceptivity for transplantation of a pre-implantation embryo.

Provided herein are methods of predicting endometrial receptivity statusfor embryonic implantation in a human subject that include: (a)providing a first biological sample obtained from a human subject at afirst time point within a menstrual cycle; (b) determining the geneexpression profile of a panel of genes in the first biological sample,wherein the panel of genes consists of: Annexin A4 (ANXA4), Cationchannel sperm auxiliary subunit beta (CATSPERB), Prostaglandin Freceptor (PTGFR), Prostaglandin-endoperoxide synthase 1 (prostaglandinG/H synthase and cyclooxygenase) (PTGS1), Interleukin-8 (IL8),Secretoglobin, family 2A, member 2 (SCGB2A2), Angiopoietin-like 1(ANGPTL1), Hypoxanthine phosphoribosyltransferase 1 (HPRT1), Matrixmetallopeptidase 10 (MMP10), Progesterone Receptor (PGR), Integrin alpha8 (ITGA8), Interferon gamma (IFNG), Prokineticin-1 (PROK1), Forkhead boxprotein O1 (FOXO1), C-X-C motif chemokine ligand 1 (CXCL1),Stanniocalcin-1 (STC1), Matrix Metallopeptidase 9 (MMP9), Mucin 1(MUC1), Ribosomal protein L13a (RPL13A), Calcitonin-related polypeptidealpha (CALCA), Integrin subunit alpha-9 (ITGA9), Rac GTPase-activatingprotein 1 (RACGAP1), Glutathione peroxidase 3 (GPX3), Proteinphosphatase 2, regulatory subunit B, gamma (PPP2R2C), Arginase 2 (ARG2),Secretoglobin, family 3A, member 1 (SCGB3A1), Aldehyde dehydrogenasefamily 1 member A3 (ALDH1A3), Apolipoprotein D (APOD), C2calcium-dependent domain-containing protein 4B (C2CD4B), Trefoil factor3 (TFF3), Aquaporin-3 (AQP3), Gap junction protein, alpha 4 (GJA4), RhoGDP-dissociation inhibitor alpha (ARHGDIA), Selectin L (SELL),Apolipoprotein L, 2 (APOL2), Metallothionein-1H (MT1H),Metallothionein-1X (MT1X), Metallothionein-1L (MT1L), Monoamine oxidaseAA (MAOA) and Metallothionein-1F (MT1F) using reverse transcriptionpolymerase chain reaction (RT-qPCR) analysis; and (c) identifying thehuman subject as having: (i) a receptive endometrial status, wherein thedetermined gene expression profile corresponds to a gene expressionprofile of the panel of genes of a receptive endometrial receptivityreference group, (ii) a non-receptive endometrial status, wherein thedetermined gene expression profile corresponds to a gene expressionprofile of the panel of genes of a non-receptive endometrial receptivityreference group, (iii) a pre-receptive endometrial status, wherein thedetermined gene expression profile corresponds to a gene expressionprofile of the panel of genes of a pre-receptive endometrial receptivityreference group, or (iv) a post-receptive endometrial status, whereinthe determined gene expression profile corresponds to a gene expressionprofile of the panel of genes of a post-receptive endometrialreceptivity reference group.

In some embodiments, the first biological sample is an endometrialbiopsy obtained from the uterine fundus.

In some embodiments, the human subject has undergone assistedreproductive treatment, and the first time point is seven days after aluteinizing hormone surge.

In some embodiments, the human subject has undergone assistedreproductive treatment, and the first time point is seven days afteradministration of human chorionic gonadotropin (hCG).

In some embodiments, the human subject has undergone hormone replacementtherapy cycles, and the first time point is five days after progesteroneimpregnation.

In some embodiments of any of the methods described herein, the methodfurther includes after identifying the human subject as having areceptive endometrial status, (d) transferring a pre-implantation embryointo the identified human subject.

In some embodiments of any of the methods described herein, the methodfurther includes after identifying the human subject as having anon-receptive endometrial status, a pre-receptive endometrial status, ora post-receptive endometrial status, (d) obtaining a second biologicalsample from the human subject at a second time point and repeating steps(b) and (c) on the second biological sample.

In some embodiments of any of the methods described herein, the methodfurther includes after identifying the human subject has having areceptive endometrial status, (e) transferring a pre-implantation embryointo the identified human subject.

In some embodiments, the second biological sample is an endometrialbiopsy obtained from the uterine fundus.

In some embodiments, the subject is identified as having apost-receptive endometrial status, and the second biological sample isobtained in another menstrual cycle one or two days before the firstbiological sample was taken in the previous menstrual cycle.

In some embodiments, the subject is identified as having a pre-receptiveendometrial status, and the second biological sample is obtained inanother menstrual cycle one or two days after the first biologicalsample was taken in the previous menstrual cycle.

In some embodiments wherein the subject is identified as having anon-receptive endometrial status, the method further includesinstructing a healthcare professional to select a treatment plan for theidentified subject.

In some embodiments wherein, the subject is identified as having anon-receptive endometrial status, the method further includes selectinga treatment plan for the identified subject. In some embodiments, thetreatment plan includes a hormone replacement therapy cycle.

In some embodiments, the subject has a history of miscarriages orstillbirths, and/or a history of fertility issues.

In some embodiments, the subject has had one or more cycles of in vitrofertilization (IVF).

In some embodiments, the subject has previously not had IVF.

In some embodiments, the determining step occurs on a chip, an array, amulti-well plate, or a tube (e.g., a microcentrifuge tube). In someembodiments, the determining step of each gene within the panel of genesis performed in a reaction volume of 0.005 μL to 100 μL. In someembodiments, the determining step of each gene within the panel of genesis performed in a reaction volume of 0.005 μL to 50 μL.

In some embodiments, the determining step is performed using acomputer-assisted algorithm. In some embodiments, the determining stepis performed using principal component analysis and/or discriminantfunctional analysis.

In some embodiments of any of the methods described herein, the methodfurther includes modifying the subject's clinical record to identify thesubject as having or not having a receptive endometrial status, ashaving or not having a post-receptive endometrial status, as having ornot having a pre-receptive endometrial status, or as having or nothaving a non-receptive endometrial status. The clinical record may bestored in any suitable data storage medium (e.g., a computer readablemedium).

Also provided herein are kits that include reagents suitable fordetermining an endometrial gene expression profile of a panel of genes,wherein the panel of genes consists of: ANXA4, CATSPERB, PTGFR, PTGS1,IL8, SCGB2A2, ANGPTL1, HPRT1, MMP10, PGR, ITGA8, IFNG, PROK1, FOXO1,CXCL1, STC1, MMP9, MUC1, RPL13A, CALCA, ITGA9, RACGAP1, GPX3, PPP2R2C,ARG2, SCGB3A1, ALDH1A3, APOD, C2CD4B, TFF3, AQP3, GJA4, ARHGDIA, SELL,APOL2, MT1H, MT1X, MT1L, MAOA and MT1F in a biological sample obtainedfrom a subject.

In some embodiments of any of the kits described herein, the kit furtherincludes reagents suitable for determining an endometrial geneexpression profile of the panel of genes for a set of reference groups,wherein the set of reference groups includes a receptive endometrialreference group, a non-receptive endometrial reference group, apre-receptive endometrial reference group and a post-receptiveendometrial reference group. In some embodiments, the biological sampleis an endometrial biopsy obtained from the uterine fundus.

In some embodiments, the reagents are suitable for reverse transcriptionpolymerase chain reaction.

In some embodiments of any of the kits described herein, the kit canfurther include a chip, an array, a multi-well plate or a tube (e.g., amicrocentrifuge tube).

In some embodiments of any of the kits described herein, the kit canfurther include instructions for use of the kit according to any of themethods described herein.

Also provided in aspects of the invention are panels of genes useful forpredicting endometrial receptivity for embryonic implantation in a humansubject. By “a panel of genes” it is meant a collection, or combination,of two or more genes, e.g., two, three, four, five, six, seven, eight,nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen,seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two,twenty-three, twenty-four, twenty-five, twenty-six, twenty-seven,twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three,thirty-four, thirty-five, thirty-six, thirty-seven, thirty-eight,thirty-nine, or forty genes, whose gene expression profile in abiological sample (e.g., an endometrial tissue biopsy sample) isassociated with endometrial receptivity. The panel of genes (e.g., panelA) described herein may be used to provide a prediction of endometrialreceptivity of a human subject, to monitor a subject with fertilityissues (e.g., recurrent miscarriages, recurrent failed cycles of invitro fertilization (IVF)), to monitor a subject undergoing IVF, toprovide a prognosis to a human subject having a receptive endometrialstatus, to provide a prognosis to a human subject having a non-receptiveendometrial status, to provide a prognosis to a human subject having apre-receptive endometrial status, to provide a prognosis to a humansubject having a post-receptive endometrial status.

In some embodiments, the methods include instructing a healthcareprofessional (e.g., a physician, physician assistant, nursepractitioner, nurse and case manager) to select a treatment plan for asubject. For example, the methods may further include selecting atreatment plan for a subject, which includes selectively administering ahormone replacement therapy (e.g., progesterone and estrogen), and/orperforming a fertility evaluation, which includes, for example,performing a procedure selected from the group consisting of: anultrasound, a hysterosalpingogram, a hysteroscopy and a hormone bloodtest. The treatment plan can include prescribing to the subjecttherapeutic lifestyle changes to improve fertility (e.g., dietarychanges, weight loss or weight gain).

As used herein, the term “biological sample” refers to a sample obtainedor derived from a subject. By way of example, the sample may be selectedfrom the group consisting of body fluids (e.g., blood, whole blood,plasma, serum, mucus secretions, urine, or saliva) and tissue (e.g., anendometrial tissue biopsy sample). In some embodiments, the sample is,or includes a blood sample. The preferred biological source is anendometrial tissue biopsy sample.

The term “subject” as used herein refers to a mammal. A subjecttherefore refers to, for example, dogs, cats, horses, cows, pigs, guineapigs, humans and the like. When the subject is a human, the subject maybe referred to herein as a patient. The human subject can be geneticallyfemale (having XX sex chromosomes, or XXY sex chromosomes),premenopausal, and/or of advanced maternal age (e.g., over 35 years ofage). For example, the human subject can have a history of miscarriagesor stillbirths, a history of fertility issues/complications (e.g.,pelvic inflammatory disease, endometriosis, polycystic ovarian syndrome,hormonal imbalances, premature ovarian aging/failure, antiphospholipidsyndrome), and/or has previously had assisted reproductive treatmentsand/or hormone replacement therapies. In some examples, the humansubject has had one or more cycles of IVF. In other examples, thesubject has not had IVF.

As used herein, “obtain” or “obtaining” can be any means whereby onecomes into possession of the sample by “direct” or “indirect” means.Directly obtaining a sample means performing a process (e.g., performinga physical method such as extraction) to obtain the sample. Indirectlyobtaining a sample refers to receiving the sample from another party orsource (e.g., a third party laboratory that directly acquired thesample). Directly obtaining a sample includes performing a process thatincludes a physical change in a physical substance, e.g., a startingmaterial, such as a tissue biopsy, (e.g., endometrial biopsy that waspreviously isolated from a patient). Thus, obtain is used to meancollection and/or removal of the sample from the subject.

As used herein the term “reference group” refers to a group ofendometrial tissue biopsy samples that are obtained from a group ofindividuals for which the endometrial status is known. A “receptiveendometrial reference group” means that the gene expression profile ofthe selected genes (e.g., panel A) is for a group of individuals with areceptive endometrial status. A “non-receptive endometrial referencegroup” means that the gene expression profile of the selected genes(e.g., panel A) is for a group of individuals with non-receptiveendometrial status. A “pre-receptive endometrial reference group” meansthat the gene expression profile of the selected genes (e.g., panel A)is for a group of individuals with pre-receptive endometrial status. A“post-receptive endometrial reference group” means that the geneexpression profile of the selected genes (e.g., panel A) is for a groupof individuals with a post-receptive endometrial status.

As used herein, the phrase “receptive endometrial status” means that thewindow of implantation matches the day on which the biopsy was taken,and that the subject's uterus is receptive for embryonic implantation.For example, a receptive endometrial status is defined as an endometrialstatus that is observed 7 days after the luteinizing hormone (LH) surgein a natural menstrual cycle of 28 days.

The phrase “pre-receptive endometrial status” means that the window ofimplantation has not yet been reached on the day on which the biopsy wastaken, and that the subject's uterus is not receptive for embryonicimplantation. A pre-receptive endometrial status is defined as anendometrial status that is observed in the days prior to the window ofimplantation during the secretory phase of a menstrual cycle.

The phrase “post-receptive endometrial status” means that the window ofimplantation has already passed on the day on which the biopsy wastaken, and that the subject's uterus is not receptive for embryonicimplantation. A post-receptive endometrial status is defined as anendometrial status that is observed in the days following the window ofimplantation during the secretory phase of a menstrual cycle.

The phrase “non-receptive endometrial status” means that the day onwhich the biopsy was taken was during the proliferative phase of amenstrual cycle, and that the subject's uterus is not receptive forembryonic implantation.

A “luteinizing hormone (LH) surge” can be determined using variousmethods known in the art, including by urine and/or blood testing, inorder to detect the expression and/or presence of LH in a sample, and/orto quantify the amount of LH present in a sample. Expression and/orpresence of LH can be detected using known assays that includeantibodies targeting LH. Kits for determining a LH surge arecommercially available and known to those in the art.

The phrase “the endometrial gene expression profile corresponds to anendometrial gene expression profile of the panel of genes of a referencegroup” means that the endometrial gene expression profile of a sample ispredicted based on computer-assisted algorithms (e.g., principlecomponent analysis, or any other classification algorithms known in theart) to fall within the classification of the endometrial geneexpression profile of a reference group (e.g., a receptive endometrialreference group, a non-receptive endometrial reference group, apre-receptive endometrial reference group, a post-receptive endometrialreference group).

As used herein, the phrase “assisted reproductive treatment (ART)”refers to a plurality of treatments that may facilitate fertilitytreatment. Non-limiting examples of ART include in vitro fertilization(IVF), gamete intrafallopian transfer (GIFT), zygote intrafallopiantransfer (ZIFT), surrogacy, pre-implantation genetic testing, in vitrooocyte maturation, and hormone replacement therapy (HRT) cycles (e.g.,exogenous administration of progesterone and estrogen).

As used herein the term “subfertile” refers to a subject who hasdifficulty getting pregnant or carrying a pregnancy to full-term. Forexample, a subject may be subfertile because of endometriosis, ovulatorydisorders, tubal disease, peritoneal adhesion, and/or uterineabnormalities. For example, a subject may be subfertile if the subjectis of advanced age (i.e. over 35 years of age).

As used herein the term “pre-implantation embryo” refers to an embryothat was fertilized in vitro. In some embodiments, a pre-implantationembryo is a blastocyst (i.e. an embryo of 5-7 days post fertilization).In some embodiments, the pre-implantation embryo was geneticallyprofiled by pre-implantation genetic screening and/or diagnosis prior totransfer to the uterus of a subject identified as having a receptiveendometrial status.

Unless otherwise defined, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention belongs. Methods and materials aredescribed herein for use in the present invention; other, suitablemethods and materials known in the art can also be used. The materials,methods, and examples are illustrative only and not intended to belimiting. All publications, patent applications, patents, sequences,database entries, and other references mentioned herein are incorporatedby reference in their entirety. In case of conflict, the presentspecification, including definitions, will control.

Other features and advantages of the invention will be apparent from thefollowing detailed description and figures, and from the claims.

DESCRIPTION OF DRAWINGS

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

FIG. 1 is a representative STRING database generated protein interactionnetwork of the proteins codified by the 184 WO1 selected genes.

FIG. 2A is a representative volcano plot of gene expression differencesfor the 184 WOI genes on days LH+2 and LH+7 of fertile subjectsmenstrual cycles. The log 2 fold change is plotted on the x-axis and thenegative log 10 p-value is plotted on the y-axis. Green dots representgene probes with P value <0.05 by paired t-test and downregulated foldchange (log 2FC<−0.5). Orange dots represent gene probes with p-value<0.05 by paired t-test and up-regulated fold change (log 2FC>0.5).

FIG. 2B is a representative bar graph showing log 2 fold changes of the85 differentially expressed mRNAs (Paired t-test, p<0.05) in LH+7 vsLH+2. 71 mRNAs were upregulated and 14 mRNAs were downregulated in LH+7compared to LH+2.

FIG. 3A is a representative chart for the variance (eigenvalue) providedby each principal component (PC) from the PCA and the cumulativepercentage along the 40 PCs. The green bars illustrate the variance ofeach PC, and the orange line illustrates the cumulative varianceexplained by the retaining PCs. The genes with the highest coefficientvalue from each component are detailed below each PC number.

FIG. 3B is a representative canonical plot using discriminant functionalanalysis with the 40 genes selected to classify 312 endometrial samples.X, Y and Z axis represent the discriminant function scores for the firstthree dimensions. Non-receptive samples are represented as blue circle,pre-receptive as green circle, receptive as orange circle andpost-receptive as purple circle.

DETAILED DESCRIPTION

The present disclosure is based, in part, on the unexpected discoverythat it is possible to determine the receptivity status of anendometrium for embryonic implantation by combined qRT-PCR expressionanalysis of genes involved in endometrial proliferation and immuneresponse.

One of the key processes for the establishment of a successful pregnancyis embryonic implantation into the endometrium. Implantation is acomplex process that involves an intricate dialogue between the embryoand the endometrial cells (Singh et al., J Endocrinol 2011; 210:5-14).This interaction is required for the apposition, adhesion and invasionof the blastocyst (Giudice and Irwin, Semin Reprod Endocrinol 1999;17:13-21).

The human endometrium is a highly dynamic structure, which undergoesperiodical changes during menstrual cycle in order to reach a receptivestatus adequate for embryonic implantation. This period of receptivityis known as the window of implantation (WOI) and occurs between Day 19and Day 21 of the menstrual cycle (Navot et al., Fertil Steril 1991;55:114-118; Harper, Baillieres Clin Obstet Gynaecol 1992; 6:351-371;Giudice, Hum Reprod 1999; 14 Suppl 2:3-16). In any other phase of themenstrual cycle, the endometrium is reluctant to pregnancy(Garrido-Gómez et al., Fertil Steril 2013; 99:1078-1085). Successfulimplantation requires therefore a viable embryo and synchrony between itand the receptive endometrium (Teh et al., J Assist Reprod Genet 2016;33:1419-1430). The correct identification and prediction of the periodof uterine receptivity is essential to maximize the effectiveness ofassisted reproduction treatments (ART).

The study of endometrial receptivity is not new as histological analysishas been traditionally used for endometrial dating (Noyes et al., FertilSteril 1950; 1:3-25); however, the accuracy of this method to predictendometrial receptivity has been shown to be limited (Coutifaris et al.,Fertil Steril 2004; 82:1264-1272; Murray et al., Fertil Steril 2004;81:1333-1343). Some alternative methods to evaluate endometrialreceptivity have been developed in the last decade, these methodsinclude: biochemical markers such as molecules involved in calciumsensing and signal transduction (Zhang et al., Reprod Biol Endocrinol2012; 10:106), soluble ligands (Thouas et al., Endocr Rev 2015;36:92-130), hormone receptors (Aghajanova et al., Fertil Steril 2009;91:2602-2610), cytokines (Jones et al., J Clin Endocrinol Metab 2004;89:6155-6167; Lédée-Bataille et al., Fertil Steril 2005; 83:598-605;Paiva et al., Hum Reprod 2011; 26:1153-1162), microRNAs (Sha et al.,Fertil Steril 2011; 96; Kresowik et al., Biol Reprod 2014; 91:20-24) orHOX-class homeobox genes (Kwon and Taylor, Ann N Y Acad Sci 2004; 1034:p. 1-18; Xu et al., Hum Reprod 2014; 29:781-790).

Other studies, focused on the understanding of the molecular mechanismsunderlying the histological changes observed in the endometrium duringthe menstrual cycle, have identified specific genes responsible for thealterations observed (Talbi et al., Endocrinology 2006; 147:1097-1121;Zhang et al., Mol Reprod Dev 2013; 80:8-21). Some other reports haveaddressed this molecular analysis from a wider perspective, performing aglobal screening of the transcriptome at different moments of themenstrual cycle (Carson, Mol Hum Reprod 2002; 8:871-879; Ponnampalam etal., Mol Hum Reprod 2004; 10:879-893; Mirkin et al., Hum Reprod 2005;20:2104-2117; Talbi et al., Endocrinology 2006; 147:1097-1121; Haouzi etal., Hum Reprod 2009; 24:198-205), under different infertilityconditions (Koler et al., Hum Reprod 2009; 24:2541-2548; Altmäe et al.,Mol Hum Reprod 2010; 16:178-187; Roy et al., Hum Reprod 2014;29:2431-2438; Tapia-Pizarro et al., Reprod Biol Endocrinol 2014; 12:92;Koot et al., Sci Rep 2016; 6:19411), pathologies (Kao et al., 2003; Sunet al., Fertil Steril 2014; 101; Garcia-Velasco et al., Reprod BiomedOnline 2015; 31:647-654) or ovarian stimulation protocols (Mirkin etal., J Clin Endocrinol Metab 2004; 89:5742-5752; Horcajadas et al., MolHum Reprod 2005; 11:195-205; Liu et al., Fertil Steril 2008;90:2152-2164; Haouzi et al., Hum Reprod 2009; 24:1436-1445). Valuableinformation about the process of endometrial proliferation can beextracted from these studies. However, even though the list of studiespublished in this topic is long, the number of molecular diagnostictools to identify the moment of uterine receptivity is reduced (Lesseyet al., Fertil Steril 1995; 63:535-542; Lessey et al., Fertil Steril2000; 73:779-787; Dubowy et al., Fertil Steril 2003; 80:146-156;Diaz-Gimeno et al., Fertil Steril 2011; 95:50-60, 60-15). Some studieslooking at the utility of single molecule markers for endometrialreceptivity have concluded that a single molecule may not suffice todescribe a complex phenomenon like receptivity (Brinsden et al., FertilSteril 2009; 91:1445-1447) and, in this sense, transcriptomic profilesmay be a more reliable tool.

Most global transcriptomic analyses of the endometrium have beenperformed using an unselected source of genes involved in manybiological processes, but not specifically expressed in the endometrialtissue or related to the process of endometrial receptivity acquisition.The selection of genes, specifically described to be expressed in theendometrium during the WOI and involved in the process of embryonicimplantation, was chosen as a better strategy to accurately define thetranscriptomic signature of the receptive endometrium and also todevelop a reliable diagnostic tool for endometrial receptivity.Processes such as endometrial proliferation and immune response havebeen described as essential for endometrial preparation and embryonicimplantation, so a selection of genes involved in those processes couldprovide interesting biological and clinical information about theprocess of endometrial receptivity (Sign et al., 2011; andHaller-Kikkatalo et al., Semin Reprod Med 2014; 32: 376-384).

For global endometrial transcriptomic analyses, the preferred techniquehas been gene expression microarrays (Sherwin et al., Reproduction 2006;132:1-10; Horcajadas et al., Hum Reprod Updat 2007; 13:77-86; Haouzi etal., Reprod Biomed Online 2012; 24:23-34).

RT-qPCR has been shown to have the widest dynamic range, the lowestquantification limits and the least biased results and hence it isconsidered the gold standard method for gene expression analysis. Inthis context, we believe the use of RT-qPCR may be a more robust andreliable technique for the analysis of the expression of genes relevantfor the process of endometrial receptivity and, also, for thedevelopment of diagnostic tools based on the identification of specificsignatures associated to different endometrial status.

Without wishing to be bound by theory, the present inventors defined anew system for human endometrial receptivity evaluation, based on theanalysis of the expression of genes related to endometrial proliferationand the immunological response associated to embryonic implantationusing a high throughput RT-qPCR platform. A comprehensive solution toanalyze the endometrial transcriptomic signature at the WOI wasexplored. Validation was achieved on 306 endometrial samples includingfertile women and patients undergoing fertility treatment between July2014 and March 2016. Expression analyses of 184 genes involved inendometrial receptivity and immune response were performed. Samples wereadditionally tested with an independent endometrial receptivity test.Gene ontology analyses revealed that cellular proliferation, response towounding, defence and immune response are the most over-representedbiological terms in the group of genes selected. Significantly differentgene expression levels (fold change) were found in 85 out of 184selected genes when comparing LH+2 and LH+7 samples (Paired t-test,p<0.05). Principal component analysis (PCA) and discriminant functionalanalysis revealed that 40 of the differentially expressed genes allowedaccurate classification of samples into 4 endometrial status:proliferative, pre-receptive, receptive and post-receptive in bothgroups, fertile women and infertile patients.

The identification of the optimal time for embryo transfer is essentialto maximize the effectiveness of assisted reproductive technologies. Forsuccessful embryo implantation, a healthy embryo at blastocyst state anda functional endometrium ready to receive it, are required. There isgrowing evidence that shows the importance of embryonic-endometrialsynchrony for the achievement of a successful pregnancy (Navot et al.,Fertil Steril 1991; 55:114-118; Prapas et al., Hum Reprod 1998;13:720-723; Wilcox et al., N Engl J Med 1999; 340:1796-1799; Shapiro etal., Fertil Steril 2008; 89:20-26; Shapiro et al., Reprod Biomed Online2014; 29:286-290; Reprod Biomed Online 2016; 33:50-55; Franasiak et al.,Fertil Steril 2013; 100:597; Healy et al., Hum Reprod 2017; 32:362-367).This concept, however, has yet to be taken into the IVF clinicalpractice. Much effort is put in the production and selection of the mostcompetent embryo to be transferred (Chen et al., Fragouli and Wells,Semin Reprod Med 2012; 30:289-301; Cruz et al., J Assist Reprod Genet2011; 28:569-573; and Forman et al., Fertil Steril 2013; 100:100-107),but little attention is paid to the other essential part of thepregnancy; no detailed analysis of the functionality of the endometriumor the period of uterine receptivity is routinely performed in IVFcenters. The identification of the optimal time for embryo transfer isessential to maximize the effectiveness of ART.

The present disclosure relates to methods useful for thecharacterization of (e.g., clinical evaluation, diagnosis,classification, prediction, or profiling) of endometrial receptivitybased on the gene expression profile of a panel of genes (e.g., panelA). The panel of genes described herein are particularly useful forcharacterizing (e.g., assessing or predicting) a subject for having areceptive status for embryonic implantation. Thus, in some aspects, thedisclosure provides methods that include determining the gene expressionprofile of a selected panel of genes in a biological sample obtainedfrom a subject, wherein a panel comprises a plurality of genesassociated with endometrial receptivity. The number of genes in theplurality of genes (e.g., at least two) of panel A may be two or more,three or more, four or more, five or more, six or more, seven or more,eight or more, nine or more, ten or more, eleven or more, twelve ormore, thirteen or more, fourteen or more, fifteen or more, sixteen ormore, seventeen or more, eighteen or more, nineteen or more, twenty ormore, twenty-one or more, twenty-two or more, twenty-three or more,twenty-four or more, twenty-five or more, twenty-six or more,twenty-seven or more, twenty-eight or more, twenty-nine or more, thirtyor more, thirty-one or more, thirty-two or more, thirty-three or more,thirty-four or more, thirty-five or more, thirty-six or more,thirty-seven or more, thirty-eight or more, or thirty-nine or more.

Moreover, the methods described herein are useful for diagnosing whethera subject has a receptive endometrial status, a non-receptiveendometrial status, a pre-receptive endometrial status, or apost-receptive endometrial status. As used herein, diagnosing includesboth diagnosing and aiding in diagnosing. Thus, other diagnosticcriteria may be evaluated in conjunction with the results of the methodsdescribed herein in order to make a diagnosis.

The disclosure further provides for the communication of the results ofthe methods described herein to, e.g., technicians, physicians, nursepractitioner or patients. In some embodiments of any of the methodsdescribed herein, the method further includes communicating theendometrial status (i.e. as having a receptive endometrial status, ashaving a non-receptive endometrial status, as having a pre-receptiveendometrial status, as having a post-receptive endometrial status) as areport. Any of the methods described herein can include a step ofgenerating or outputting a report providing the results of any of themethods described herein. This report can be provided in the form of atangible medium (e.g., a report printed on a paper or other tangiblemedium), in the form of an electronic medium (e.g., an electronicdisplay on a computer monitor), or communicated by phone. In someembodiments, computers are used to communicate results of the methodsdescribed herein or predictions, or both, to interested parties, e.g.,physicians and their patients.

The methods described herein can be used alone or in combination withother clinical methods for endometrial receptivity stratification knownin the art to provide a diagnosis, a prognosis, or a prediction ofendometrial receptivity. For example, clinical parameters that are knownin the art for predicting endometrial receptivity may be incorporatedinto the analysis of one of ordinary skill in the art to arrive at anendometrial receptivity assessment with any of the methods describedherein.

Methods of Predicting

Also provided herein are methods of predicting endometrial receptivityfor embryonic implantation in a human subject that include: (a)providing a first biological sample obtained from a human subject at afirst time point within a menstrual cycle; (b) determining the geneexpression profile of a panel of genes in the first biological sample,wherein the panel of genes consists of: ANXA4, CATSPERB, PTGFR, PTGS1,IL8, SCGB2A2, ANGPTL1, HPRT1, MMP10, PGR, ITGA8, IFNG, PROK1, FOXO1,CXCL1, STC1, MMP9, MUC1, RPL13A, CALCA, ITGA9, RACGAP1, GPX3, PPP2R2C,ARG2, SCGB3A1, ALDH1A3, APOD, C2CD4B, TFF3, AQP3, GJA4, ARHGDIA, SELL,APOL2, MT1H, MT1X, MT1L, MAOA and MT1F using reverse transcriptionpolymerase chain reaction analysis; and (c) identifying the humansubject as having: (i) a receptive endometrial status, wherein thedetermined gene expression profile corresponds to a gene expressionprofile of the panel of genes of a receptive endometrial receptivityreference group (ii) a non-receptive endometrial status, wherein thedetermined gene expression profile corresponds to a gene expressionprofile of the panel of genes of a non-receptive endometrial referencegroup, (iii) a pre-receptive endometrial status, wherein the determinedgene expression profile corresponds to a gene expression profile of thepanel of genes of a pre-receptive endometrial reference group, or (iv) apost-receptive endometrial status, wherein the determined geneexpression profile corresponds to a gene expression profile of the panelof genes of a post-receptive endometrial receptivity reference group.

In some aspects, the methods can include transferring pre-implantationembryo into the identified human subject. In other aspects, the methodscan include obtaining a second biological sample from the human subjectat a second time point and repeating steps (b) and (c) on the secondbiological sample.

Methods of Determining

As used herein, an endometrial gene expression profile using theselected 40 genes (i.e. panel A) can be determined using anyquantitative real-time PCR machine (e.g., a Biomark HD™ System(Fluidigm®)). In some aspects, determining an endometrial geneexpression profile of a biological sample (e.g., an endometrial biopsysample) can include: extracting RNA from the biological sample,performing reverse transcription to generate cDNA, contacting thegenerated cDNA with pairs of primers targeting the genes of panel A andthe control genes, collecting gene expression data using real-time PCRanalysis software, performing principal component analysis (PCA) and/ordiscriminant functional analysis (DA) to determine the endometrialreceptivity status of the biological sample as compared to the geneexpression profile of panel A of a reference group (e.g., the receptiveendometrial reference group, the non-receptive endometrial referencegroup, the pre-receptive endometrial reference group, the post-receptiveendometrial reference group).

Each reverse transcription PCR reaction occurs in a reaction volume thatincludes all of the components required to carry out a reaction, e.g.,primers, buffer, DNA polymerase, reverse transcriptase, sample. Thedetermining step of each gene within the panel of genes is performed ina reaction volume of 0.005 μL to 100 μL (e.g., 0.005 μL, to 100 μL,0.005 μL, to 90 μL, 0.005 μL to 80 μL, 0.005 μL to 70 μL, 0.005 μL, to60 μL, 0.005 μL, to 50 μL, 0.005 μL, to 40 μL, 0.005 μL to 30 μL, 0.005μL, to 20 μL, 0.005 μL to 10 μL, 0.01 μL to 100 μL, 0.01 μL, to 90 μL,0.01 μL, to 80 μL, 0.01 μL to 70 μL, 0.01 μL to 60 μL, 0.01 μL to 50 μL,0.01 μL to 40 μL, 0.01 μL to 30 μL, 0.01 μL to 20 μL, 0.01 μL to 10 μL,0.02 μL to 100 μL, 0.02 μL to 90 μL, 0.02 μL to 80 μL, 0.02 μL to 70 μL,0.02 μL to 60 μL, 0.02 to 50 μL, 0.02 to 40 μL, 0.02 to 30 μL, 0.02 μLto 20 μL, 0.02 μL to 10 μL, 0.05 μL to 100 μL, 0.05 μL to 90 μL, 0.05 μLto 80 μL, 0.05 μL to 70 μL, 0.05 μL to 60 μL, 0.05 μL to 50 μL, 0.05 μLto 40 μL, 0.05 μL to 30 μL, 0.05 μL to 20 μL, 0.05 μL to 10 μL, 1 μL to100 μL, 1 μL to 90 μL, 1 μL to 80 μL, 1 μL to 70 μL, 1 μL to 60 μL, 1 μLto 50 μL, 1 μL to 40 μL, 1 μL to 30 μL, 1 μL to 20 μL, 1 μL to 10 μL, 5μL to 100 μL, 5 μL to 90 μL, 5 μL to 80 μL, 5 μL to 70 μL, 5 μL to 60μL, 5 μL to 50 μL, 5 μL to 40 μL, 5 μL to 30 μL, 5 μL to 20 μL, 5 μL to10 μL, 10 μL to 100 μL, 10 μL to 90 μL, 10 μL to 80 μL, 10 μL to 70 μL,10 μL to 60 μL, 10 μL to 50 μL, 10 μL to 40 μL, 10 μL to 30 μL, 10 μL to20 μL, 15 μL to 100 μL, 15 μL to 90 μL, 15 μL to 80 μL, 15 μL to 70 μL,15 μL to 60 μL, 15 μL to 50 μL, 15 μL to 40 μL, 15 μL to 30 μL, 15 μL to20 μL, 20 μL to 100 μL, 20 μL to 90 μL, 20 μL to 80 μL, 20 to 70 μL, 20μL to 60 μL, 20 to 50 μL, 20 to 40 μL, 20 to 30 μL, 50 μL to 100 μL, 50to 90 μL, 50 to 80 μL, 50 to 70 μL, 50 to 60 μL, 25 μL to 100 μL, 30 μLto 100 μL, 40 μL to 100 μL, 50 μL to 100 μL, 60 μL to 100 μL, 70 μL to100 μL, 80 μL to 100 μL, 90 μL to 100 μL).

Methods of digesting a tissue sample (e.g., an endometrial biopsysample) and extracting RNA from a tissue sample are well-known in theart and are described herein.

As used herein, the term “principal component analysis” or “principalcomponent algorithm” refers to a statistical method that uses anorthogonal transformation to convert a set of observations of possiblycorrelated variables into a set of values of linearly uncorrelatedvariables called principal components. It finds the principal componentsof the dataset and transforms the data into a new, lower-dimensionalsubspace. The principle component, which can be represented by aneigenvector, mathematically corresponds to a direction in the originaln-dimensional space, so that the first principal component accounts foras much of the variance in the data as possible, and each succeedingcomponent accounts for as much of the remaining variance as possible.

Principal component analysis (PCA) is a statistical method that uses anorthogonal transformation to convert a set of observations of possiblycorrelated variables into a set of values of linearly uncorrelatedvariables called principal components. It finds the principal componentsof the dataset and transforms the data into a new, lower-dimensionalsubspace. The transformation is defined in such a way that the firstprincipal component has the largest possible variance (that is, accountsfor as much of the variability in the data as possible), and eachsucceeding component in turn has the highest variance possible under theconstraint that it is orthogonal to the preceding components. Theresulting vectors are an uncorrelated orthogonal basis set. PCA issensitive to the relative scaling of the original variables.

Mathematically, the principal components are the eigenvectors of thecovariance or correlation matrix of the original dataset. As thecovariance matrix or correlation matrix is symmetric, the eigenvectorsare orthogonal. The principal components (eigenvectors) correspond tothe direction (in the original n-dimensional space) with the greatestvariance in the data. Each eigenvector has a corresponding eigenvalue.An eigenvalue is a scalar. The corresponding eigenvalue is a number thatindicates how much variance there is in the data along that eigenvector(or principal component). A large eigenvalue means that that principalcomponent explains a large amount of the variance in the data.Similarly, a principal component with a very small eigenvalue explains asmall amount variance in the data.

Detailed descriptions regarding how to perform PCA are described innumerous references, e.g., Smith, Lindsay I. “A tutorial on principalcomponents analysis.” Cornell University, USA 51 (2002): 52; Shlens,Jonathon. “A tutorial on principal component analysis.” arXiv preprintarXiv:1404.1100 (2014), each of which is incorporated by reference inits entirety.

To apply principle component analysis for the disclosed methods, a setof data comprising expression profile of a panel of genes is created foreach sample. The set of data for a sample can be represented by avector. The dataset can include the expression profile for all subjectsin reference group of interest (e.g., a receptive endometrial referencegroup, a non-receptive endometrial reference group, a pre-receptiveendometrial reference group, a post-receptive endometrial referencegroup) and/or the expression profile of the panel of the genes fortested subjects. The principal component analysis (PCA) converts thedataset into a dataset with lower dimensions. The positions of the eachsubject (including subjects in the reference group and the testedsubject) are determined in this lower dimensional space. In this lowerdimension space, if the tested subject is closer to, or is clusteredwith a particular reference group, then it can be determined that thistested subject corresponds to this particular reference group.

The methods to determine whether a test subject is closer to, or isclustered with, a particular reference group are known in the art, andcan be determined by algorithms known in the art, e.g., hierarchicalclustering algorithm, k-means clustering algorithm, a statisticaldistribution model, etc. Various computer algorithms for data analysisand classification are known in the art to compare gene expressionprofiles. See, e.g., Diaz-Gimeno et al., Fertil Steril 2011 95(1):50-60; Diaz-Gimeno et al., Fertil Steril 2013; 99: 508-517.

Kits

Also provided herein are kits that include any of the reagents suitablefor predicting endometrial receptivity for transplantation of apre-implantation embryo. The kits include reagents suitable fordetermining an endometrial gene expression profile of a panel of genes(e.g., panel A). In some embodiments, the kits can include instructionsfor performing use of the kit in the methods described herein. In someembodiments, the reagents suitable for determining the endometrial geneexpression profile of the biological sample are disposed in an array, achip, a multi-well plate (e.g., a 96-well plate or a 384-well plate), ora tube (e.g., a 0.2 mL microcentrifuge tube). In some embodiments of anyof the kits described herein, the kit includes an array, a chip, amulti-well plate (e.g., a 96-well plate or a 384-well plate), or a tube(e.g., a 0.2 mL microcentrifuge tube). In some embodiments of any of thekits described herein, the kit includes one or more reference groups(e.g., the receptive endometrial reference group, the non-receptiveendometrial reference group, the pre-receptive endometrial referencegroup, the post-receptive endometrial reference group) for determiningendometrial gene expression profile of a sample based oncomputer-assisted algorithms (e.g., principle component analysis, or anyother classification algorithms known in the art). In some cases, thekits include software useful for comparing the endometrial geneexpression profile of a sample with a reference group (e.g., aprediction model). The software may be provided in a computer readableformat (e.g., a compact disc, DVD, flash drive, zip drive etc.), or thesoftware may be available for downloading via the internet. The kitsdescribed herein are not so limited; other variations will be apparentto one of ordinary skill in the art.

EXAMPLES

The invention is further described in the following examples, which donot limit the scope of the invention described in the claims.

Example 1. Endometrial Receptivity Testing on Biomark HD™ System(Fluidigm®)

Study Design

In order to define the method for endometrial receptivity evaluation,gene expression data from endometrial biopsies obtained at differentmoments of the menstrual cycle from healthy fertile donors (group A) andsubfertile women (group B) were analyzed. Endometrial biopsies fromgroup A were used to define endometrial receptivity transcriptomicsignature. Endometrial samples from group B were tested and diagnosedfor receptivity according to the methods described herein and theendometrial receptivity array ERA® (Igenomix, Spain). Receptivity statusconcordance between the present method and ERA classification wasevaluated in this group of samples.

Patient Selection and Sample Collection

Group A consisted of 96 healthy fertile donors (aged between 18 and 34years), with regular menstrual cycles and normal body mass indicator(BMI) (25-30). Endometrial biopsies from this group were obtained on twodifferent days of the same natural menstrual cycle: LH+2, i.e. two daysafter the luteinizing hormone (LH) surge and LH+7, i.e. 7 days after theLH surge. Group B consisted of 120 subfertile patients (aged 30-42years) seeking ART treatment and undergoing hormone replacement (HRT)cycles. Endometrial biopsies from this group of patients were obtainedafter 5 full days of progesterone impregnation (P₄+5).

Endometrial biopsies were obtained from the uterine fundus using aPipelle catheter (Gynetics, Namont-Achel, Belgium) under sterileconditions. A piece of endometrial tissue of approximately 30 mg wasobtained per donor or subfertile patient. The day of the biopsy wascalculated in natural cycles as the number of days after the LH surge.The day of the LH surge was considered LH+0. LH urine levels weremeasured daily using a commercially available detection kit (Clearblue,SPD Swiss Precision Diagnostics; Geneva, Switzerland). In HRT cycles,the day of the biopsy was calculated as the number of days after thefirst progesterone intake. The day of the first progesterone intake isconsidered P₄+0. After endometrial biopsy collection, tissue was placedin a CryoTube® (Nunc, Roskilde, Denmark) containing 1 ml RNAlater®(Sigma-Aldrich, St Louis, Mo., USA) and stored at −20° C. until furtherprocessing. Ethical approval for the study was obtained from CentroHospital Universitario Virgen del Rocio (Sevilla, Spain, CEI#2014PI/025). All fertile donors and subfertile patients signed aninformed consent document.

Reference Genes Selection

Eight candidate reference genes were selected: actin (ACTN), beta-2microglobulin (B2M), cytochrome C1 (CYC1), EMG1 N1-specificpseudouridine methyltransferase (EMG1), glyceraldehyde-3-phosphatedehydrogenase (GAPDH), TATA-box binding protein (TBP), topoisomerase(DNA) I (TOPI) and tyrosine 3-monooxygenase/tryptophan 5-monooxygenaseactivation protein zeta (YWHAZ). The expression stability of thesereference genes was calculated using the two freeware MicrosoftExcel-based applications GeNorm (Vandesompele et al., Genome Biol 2002;3:34-1) and NormFinder (Andersen et al., Cancer Res 2004; 64:5245-5250)by following the software developer's manual.

RNA Extraction and cDNA Preparation

Total RNA was extracted using RNeasy mini kit (Qiagen, London, UK)following manufacturer's instructions. RNA purity and concentration wasconfirmed by NanoDrop 2000 Spectrophotometer (Thermo Scientific,Waltham, Mass., USA) and RNA integrity was assessed using AgilentBioanalyzer 2100 (Agilent Technologies, Santa Clara, Calif., USA)according to standard protocol provided by the manufacturer. Each totalRNA sample was diluted into 250 ng/μl and reverse transcribed into cDNAusing Fluidigm® Reverse Transcription Master Mix (Fluidigm®, SanFrancisco, Calif., USA) following the instructions of the supplier. ThecDNA samples were immediately used or stored at −20° C. until furtherdownstream processing for analysis on the BioMark HD™ platform.

Gene Expression Analysis

Pairs of primers targeting the selected and reference genes weredesigned using the software platform D3 Assay Design (Fluidigm®, SanFrancisco, Calif.) and obtained from DELTAGene™ (Fluidigm®, SanFrancisco, Calif.). Specific target amplification (STA) was carried outon cDNA samples using Fluidigm® PreAmp Master Mix and DELTAgene assays(Fluidigm®, San Francisco, Calif.) following the manufacturer'sinstructions. RT-qPCR reactions were performed following the Fast GeneExpression Analysis Using Evagreen on the Biomark HD™ System, AdvancedDevelopment Protocol (PN 100-3488, Rev.C1) (Fluidigm®, San Francisco,Calif.) and 96.96 Dynamic Array™ IFC. The BioMark™ HD System usesmicrofluidic distribution of samples and requires approximately 7 nL perreaction. Data was collected with Fluidigm® Real-Time PCR analysissoftware using linear baseline correction method and global auto Cqthreshold method. Data were then exported to Excel as .csv files and Cqvalues normalized using the 3 reference genes included in the analysis.

Principal Component Analysis (PCA) and Discriminant Functional Analysis

Differential expression of genes in the proliferative and secretoryphases was assessed by comparing ΔCq values from LH+2 and LH+7 groups.In order to define the genes that had altered mRNA abundance among thegroups, a paired t-test (p<0.05) was performed. Fold change (−ΔΔCq) wascalculated to determine up-regulated and down regulated genes in theWOI. In order to assess if receptivity status could be established witha reduced number of genes, a principal component analysis (PCA) of thegenes showing significant fold change between LH+2 and LH+7 wasperformed. Discriminant functional analysis (DA) was then used toevaluate the ability of the genes with the highest absolute coefficientvalue from each of the leading principal components to accuratediscriminate samples into the following states: proliferative,receptive, pre-receptive and post-receptive. A Split-Sample validationof the DA was performed to assess the reliability and robustness ofdiscriminant findings. Both fertile and infertile patient samples weresplit into two subsets. One data set (70% of the samples) was used as atraining set and the other one as testing set (remaining 30% of thesamples). The percentage of correct classifications was calculated todetermine the reliability of the DA model. Data analyses were performedby using IBM SPSS Statistics software version 19.0.

Gene Function Analysis

To study the biological functions and pathways of the genes selected,DAVID v.6.7 bioinformatics resources were used (Huang et al., NucleicAcids Res 2009; 37:1-13). Assessment and integration of protein-proteininteractions was performed by the Search Tool for the Retrieval ofInteracting Genes/Proteins (STRING v.10.0 database (Szklarczyk et al.,Nucleic Acids Res 2015; 43:D447D452).

Results: Gene Expression, Principal Component Analysis (PCA) andDiscriminant Functional Analysis

A total of 184 genes related to endometrial receptivity and embryonicimplantation were carefully chosen after extensive literature review(Table 1).

TABLE 1 Panel of Selected Genes Gene Symbol Gene Name Reference NCBIAccession No. ABCC3 ATP-binding cassette, Díaz-Gimeno NM_003786.3sub-family C et al. 2011 (CFTR/MRP), member 3 ACTA1 Actin, alphaskeletal Altmäe et al. NM_001100.3 muscle 2010 ALDH1A3 Aldehydedehydrogenase Dominguez et NM_000693.3 family 1 member A3 al. 2009;Haouzi et al 2009, 2013 AMIGO2 Adhesion molecule with Díaz-GimenoNM_001143668.1 Ig-like domain 2 et al. 2011 ANGPTL1 Angiopoietin-like 1Haouzi et al NM_004673.3 2009, 2012 ANXA2 Annexin A2 Dominguez etNM_001002857.1 al. 2009; Haouzi et al. 2012; Tracey et al. 2013 ANXA4Annexin A4 Li et al. 2006; NM_001153.4 Chen et al 2009; Díaz- Gimeno etal. 2011; Ruíz- Alonso et al. 2012; Haouzi et al. 2012; Tracey et al.2013 APOD Apolipoprotein D Ruíz-Alonso NM_001647.3 et al. 2012 APOEApolipoprotein E Ruíz-Alonso NM_001302688.1 et al. 2012 APOL2Apolipoprotein L, 2 Dominguez et NM_030882.3 al. 2009; Haouzi et al2009, 2013 AQP3 Aquaporin-3 Díaz-Gimeno NM_004925.4 et al. 2011;Ruíz-Alonso et al. 2012 AREG Amphiregulin Aghajanova NM_001657.3 et al.2008; Barnea et al. 2012 ARG2 Arginase 2 Díaz-Gimeno NM_001172.3 et al.2011 ARHGDIA Rho GDP-dissociation Chen et al. NM_001185077.2 inhibitor(GDI) alpha 2009; Tracey et al. 2013 ATP5B ATP synthase, H+ Sadek et al.NM_001686.3 transporting, 2012 mitochondrial F1 complex, betapolypeptide BTC Probetacellulin Barnea et al. NM_001729.3 2012 C2CD4B C2calcium-dependent Haouzi et al. NM_001007595.2 domain-containing 2009,2012 protein 4B C4BPA Complement component Díaz-Gimeno NM_000715.3 4binding protein, alpha et al. 2011 CALCA Calcitonin-related Otsuka etal., NM_001033953.2 polypeptide alpha 2007 CALR Calreticulin Parmar etal. NM_004343.3 2009; Tracey et al. 2013 CAPN6 Calpain-6 Altmäe et al.NM_014289.3 2010; Díaz- Gimeno et al. 2011 CATSPERB Cation channel spermDíaz-Gimeno NM_024764.3 auxiliary subunit beta et al. 2011 CCL2Chemokine (C-C motif) Barnea et al. NM_002982.3 ligand 2 2012 CCR7Chemokine (C-C motif) Altmäe et al. NM_001838.3 receptor 7 2010 CD55CD55 molecule, decay Ruíz-Alonso NM_000574.4 accelerating factor for etal. 2012 complement (Cromer blood group) CDA Cytidine deaminaseDíaz-Gimeno NM_001785.2 et al. 2011 CDH1 Cadherin-1, type Banerjee etal. NM_004360.4 1, Epitelial-Cadherin 2013 CIR1 Corepressor interactingRuíz-Alonso NM_004882.3 with RBPJ 1 et al. 2012 CLDN4 Claudin-4Ruíz-Alonso NM_001305.4 et al. 2012 CLIC1 Chloride intracellular Chen etal. NM_001287593.1 channel protein 1 2009; Tracey et al. 2013 CLUClusterin Díaz-Gimeno NM_001831.3 et al. 2011 CMTM5 CKLF-like MARVELAltmäe et al. NM_138460.2 transmembrane domain- 2010 containing protein5 COL16A1 Collagen, type XVI, Altmäe et al. NM_001856.3 alpha 1 2010;Díaz- Gimeno et al. 2011 CRHR2 Corticotropin-releasing MakrigianakisNM_001883.4 factor receptor 2 et al. 2004 CRISP3 Cysteine-rich secretoryDíaz-Gimeno NM_006061.3 protein 3 et al. 2011; Ruíz-Alonso et al. 2012CSF1 Colony stimulating factor Gargiulo et al. NM_000757.5 1(macrophage) 2004; Aghajanova et al. 2008; Tawfeek et al. 2012 CSF3Colony stimulating factor Lédée et al. NM_000759.3 3 (granulocyte) 2011CSRP2 Cysteine and glycine-rich Díaz-Gimeno NM_001321.2 protein 2 et al.2011 CTNNA2 Catenin alpha-2 Altmäe et al. NM_001282597.2 2010; Díaz-Gimeno et al. 2011 CXCL1 Growth-regulated alpha Barnea et al.NM_001511.3 protein 2012 CXCL14 C—X—C motif chemokine Díaz-GimenoNM_004887.4 14 et al. 2011; Ruíz-Alonso et al. 2012 CXCL6 C—X—C motifchemokine Altmäe et al. NM_002993.3 6 (Chemokine alpha 3) 2010 DEFB1Beta-defensin 1 Díaz-Gimeno NM_005218.3 et al. 2011 DKK1 Dickkopf WNTsignaling Díaz-Gimeno NM_012242.3 pathway inhinitor 11 et al. 2011;Ruíz-Alonso et al. 2012 EGF Epidermal Growth Factor Gargiulo et al.NM_001963.5 2004; Aghajanova et al. 2008; Sing et al. 2011; Barnea etal. 2012 EPHB3 EPH receptor B3 Díaz-Gimeno NM_004443.3 et al. 2011 EREGProepiregulin Barnea et al. NM_001432.2 2012 ESR1 Estrogen receptor 1Gao et al. NM_000125.3 2012 ESR2 Estrogen Receptor 2 (ER Altmäe et al.NM_001437.2 Beta) 2010 EZR Ezrin Chen et al. NM_003379.4 2009; Tracey etal. 2013 FAM3B Family with sequence Altmäe et al. NM_058186.3 similarity3, member B 2010 FAM3D Family with sequence Altmäe et al. NM_138805.2similarity 3, member D 2010 FASLG Fas ligand (TNF MakrigianakisNM_000639.2 superfamily, member 6) et al. 2004 FGF7 Fibroblast growthfactor 7 Cavagna et al. NM_002009.3 2003 FOXO1 Forkhead box protein O1Ruíz-Alonso NM_002015.3 et al. 2012 FOXP3 Forkhead box protein P3 Chenet al. NM_014009.3 2012 FUT4 Fucosyltransferase 4 Liu et al. NM_002033.3(alpha (1,3) 2012 fucosyltransferase, myeloid-specific FZD5 Frizzled-5Liu et al. NM_003468.3 2010 GABARAPL1 Gamma-aminobutyric Díaz-GimenoNM_031412.2 acid (GABA(A) receptor- et al. 2011 associated protein-like1 GADD45A Growth arrest and DNA Díaz-Gimeno NM_001924.3 damage-inducibleprotein et al. 2011; GADD45 alpha Ruíz-Alonso et al. 2012 GAST GastrinDíaz-Gimeno NM_000805.4 et al. 2011 GDF15 Growth differentiationDíaz-Gimeno NM_004864.3 factor 15 et al. 2011 GJA4 Gap junction protein,Ruíz-Alonso NM_002060.2 alpha 4, 37 kDa et al. 2012 GNLY GranulysinDíaz-Gimeno NM_001302758.1 et al. 2011; Ruíz-Alonso et al. 2012 GPX3Glutathione peroxidase 3 Díaz-Gimeno NM_002084.4 et al. 2011;Ruíz-Alonso et al. 2012 HBA1 Hemoglobin, alpha 1 Altmäe et al.NM_000558.4 2010 HBEGF Heparin Binding-EGF- Stavreus- NM_001945.2 likegrowth factor Evers et al. 2002; Aghajanova et al. 2008; Altmäe et al.2010; Sing et al. 2011; Barnea et al. 2012 HBG1 Hemoglobin, gamma AAltmäe et al. NM_000559.2 2010 HMBS Hydroxymethylbilane VestergaardNM_000190.3 synthase et al. 2011 HOXA10 Homeobox A10 AghajanovaNM_018951.3 et al. 2008; Wei et al. 2009; Kakmak et al. 2011; Ruíz-Alonso et al. 2012; Garrido- Gómez et al. 2013; Jana et al. 2013 HOXA11Homeobox A11 Lynch et al., NM_005523.5 2009 HOXB7 Homeobox B7Ruíz-Alonso NM_004502.3 et al. 2012 HPRT1 Hypoxanthine VestergaardNM_000194.2 phosphoribosyltransferase 1 et al. 2011 HPSE HeparanaseDíaz-Gimeno NM_006665.5 et al. 2011 ICAM1 Intercellular adhesion Zhao etal., NM_000201.2 molecule 1 2010 ID4 DNA-binding protein Díaz-GimenoNM_001546.3 inhibitor ID-4 et al. 2011; Ruíz-Alonso et al. 2012 IDH1Isocitrate dehydrogenase Díaz-Gimeno NM_005896.3 1 (NADP+), soluble etal. 2011 IER3 Immediate early response 3 Díaz-Gimeno NM_003897.3 et al.2011 IFNG Interferon gamma Banerjee et al. NM_000619.2 2013 IGFBP1Insulin-like growth Altmäe et al. NM_000596.3 factor-binding protein 12010; Díaz- Gimeno et al. 2011 IGFBP3 Insulin-like growth Ruíz-AlonsoNM_001013398.1 factor-binding protein 3 et al. 2012 IL10 Interleukin 10Banerjee et al. NM_000572.2 2013 IL11 Interleukin 11 Altmäe et al.NM_000641.3 2010; Sing et al. 2011; Tawfeek et al. 2012 IL15Interleukin-15 Lédée et al. NM_000585.4 2011; Díaz- Gimeno et al. 2011;Ruíz- Alonso et al. 2012 IL18 Interleukin-18 Lédée et al. NM_001562.32011 IL1B Interleukin 1 Beta Gargiulo et al. NM_000576.2 2004;Aghajanova et al. 2008; Altmäe et al. 2010; Cheong et al. 2012; Koot etal. 2012; Banerjee et al. 2013 IL1R1 Interleukin-1 Receptor Garrido-NM_001288706.1 type Gómez et al. 2013 IL2 Interleukin 2 Banerjee et al.NM_000586.3 2013 IL21 Interleukin-21 Altmäe et al. NM_021803.3 2010 IL4Interleukin 4 Banerjee et al. NM_000589.3 2013 IL5 Interleukin 5(colony- Teklenburg et NM_000879.2 stimulating factor, al., 2010eosinophil) IL6 Interleukin 6 Sing et al. NM_000600.4 2011; Cheong etal. 2012; Koot et al. 2012; Barnea et al. 2012; Tawfeek et al. 2012 IL8Interleukin 8 Banerjee et al. NM_000584.3 2013 ITGAV Integrin, alpha VLessey et al., NM_002210.4 2000; Nardo et al. 2003; Aghajanova et al.2008; Barnea et al. 2012; Ruíz- Alonso et al. 2012; Koot et al. 2012;Jana et al. 2013; Tracey et al. 2013 ITGA2 Integrin, alpha 2 (CD49B,Barnea et al. NM_002203.3 alpha 2 subunit of VLA-2 2012 receptor) ITGA8Integrin, alpha 8 Altmäe et al. NM_003638.2 2010 ITGA9 Integrin, alpha 9Barnea et al. NM_002207.2 2012 ITGB1 Integrin, beta 1 Barnea et al.NM_002211.3 2012 ITGB3 Integrin, beta 3 Barnea et al. NM_000212.2 2012KCNG1 Potassium voltage-gated Díaz-Gimeno NM_002237.3 channel subfamilyG et al. 2011 member 1 LCP1 Lymphocyte cytosolic Dominguez etNM_002298.4 protein (L-plastin) al. 2009; Haouzi et al. 2009, 2013 LEPLeptin Labarta et al., NM_000230.2 2011 LIF Leukaemia InhibitorAghajanova NM_002309.4 Factor et al. 2003; Gargiulo et al. 2004;Aghajanova et al. 2008; Altmäe et al. 2010; Sing et al. 2011;Díaz-Gimeno et al. 2011; Tawfeek et al. 2012; Ruíz- Alonso et al. 2012;Tawfeek et al. 2012; Jana et al. 2013; Garrido- Gómez et al. 2013 LIFRLeukemia inhibitory Aghajanova NM_001127671.1 factor Receptor alpha etal. 2003; Aghajanova et al. 2008; Tawfeek et al. 2012 LPAR3Lysophosphatidic acid Wei et al. NM_012152.2 receptor 3 2009 LRPPRCLeucine-rich PPR motif- Tawfeek et NM_133259.3 containing protein al.,2012; Tracey et al. 2013 LRRC17 Leucine-rich repeat- Díaz-GimenoNM_001031692.2 containing protein 17 et al. 2011 LYPD3 Ly6/PLAUR domain-Díaz-Gimeno NM_014400.2 containing protein 3 et al. 2011 MAOA Monoamineoxidase A Dominguez et NM_000240.3 al. 2009; Díaz-Gimeno et al. 2011;Ruíz-Alonso et al. 2012; Haouzi et al. 2012 MAP2K1 Mitogen-activatedprotein Barnea et al. NM_002755.3 kinase 1 2012 MAP3K5 Mitogen-activatedprotein Ruíz-Alonso NM_005923.3 kinase 5 et al. 2012 MAPK1Mitogen-activated protein Barnea et al. NM_002745.4 kinase 1 2012 MAPK3Mitogen-activated protein Barnea et al. NM_002746.2 kinase 3 2012 MAPK8Mitogen-activated protein Barnea et al. NM_001278547.1 kinase 8 2012MFAP5 Microfibrillar-associated Haouzi et al. NM_003480.3 protein 52009, 2012; Díaz-Gimeno et al. 2011 MMP10 Matrix metallopeptidase Altmäeet al. NM_002425.2 10 (Stromelysin-2) 2010 MMP2 Matrix MetalloproteinaseBanerjee et al. NM_004530.5 2 (gelatinase A, 72 kDA 2013 gelatinase, 72kDA type IV collagenase) MMP26 Matrix metallopeptidase Altmäe et al.NM_021801.4 26 2010; Ruíz- Alonso et al. 2012 MMP8 Matrixmetallopeptidase 8 Altmäe et al. NM_002424.2 (Neutrophil collagenase)2010 MMP9 Matrix Metallopeptidase9 Banerjee et al. NM_004994.2(gelatinase B, 92 kDa 2013 gelatinase, 92 kDa type IV collagenase) MT1EMetallothionein 1E Ruíz-Alonso NM_175617.3 et al. 2012 MT1FMetallothionein 1F Ruíz-Alonso NM_005949.3 et al. 2012 MT1GMetallothionein 1G Díaz-Gimeno NM_001301267.1 et al. 2011; Ruíz-Alonsoet al. 2012 MT1H Metallothionein 1H Ruíz-Alonso NM_005951.2 et al. 2012MT1L Metallothionein 1L Ruíz-Alonso NR_001447.2 et al. 2012 MT1XMetallothionein 1X Ruíz-Alonso NM_005952.3 et al. 2012 MT2AMetallothionein 2 Díaz-Gimeno NM_005953.4 et al. 2011; Ruíz-Alonso etal. 2012 MUC1 Mucin 1, cell surface Altmäe et al. NM_002456.5 associated2010; Koot et al. 2012; Garrido- Gómez et al. 2013 MUC16 Mucin-16, cellsurface Altmäe et al. NM_024690.2 associated 2010; Díaz- Gimeno et al.2011 MUC4 Mucin-4, cell surface Aghajanova NM_018406.6 associated et al.2008; Altmäe et al. 2010 MUC5B Mucin-5B, oligomeric AghajanovaNM_002458.2 mucus/gel-forming et al. 2008; Altmäe et al. 2010 NFKB1Nuclear factor of kappa Barnea et al. NM_003998.3 light polypeptide 2012enhancer in B cells 1 NFKBIA Nuclear factor of kappa Barnea et al.NM_020529.2 light polypeptide 2012 enhancer in B cells inhibitor, alphaNFKBIE Nuclear factor of kappa Barnea et al. NM_004556.2 lightpolypeptide 2012 enhancer in B cells inhibitor, epsilon NNMTNicotinamide N- Díaz-Gimeno NM_006169.2 methyltransferase et al. 2011OPRK1 Opiod receptor, kappa 1 Díaz-Gimeno NM_000912.4 et al. 2011 PAEPProgestagen-associated Stavreus- NM_001018049.2 endometrial proteinEvers et al. 2006; Aghajanova et al. 2008; Wei et al. 2009; Díaz- Gimenoet al. 2011, Ruíz- Alonso et al. 2012; Ming- Qing et al. 2013 PGRProgesterone Receptor Stavreus- NM_000926.4 Evers et al. 2001;Aghajanova et al. 2008; Gao et al. 2012 PGRMC1 Progesterone receptorChen et al. NM_006667.4 membrane component 1 2009; Tracey et al. 2013PLA2G16 Phospholipase A2, group Díaz-Gimeno NM_007069.3 XVI et al. 2011PLA2G4A Phospholipase A2, group Berlanga et NM_024420.2 IVA (cytosolic,calcium- al. 2011 dependent) PPP2R2C Protein phosphatase 2, Barnea etal. NM_020416.3 regulatory subunit B, 2012 gamma PRDX1 Peroxiredoxin 1Stavreus- NM_002574.3 Evers et al. 2002; Aghajanova et al. 2008 PRDX2(Peroxiredoxin 2 Stavreus- NM_005809.5 Evers et al. 2002; Aghajanova etal. 2008 PRKCG Protein kinase C, gamma Altmäe et al. NM_001316329.1 2010PROK1 Prokineticin-1 Haouzi et al NM_032414.2 2009, 2012 PTGER3Prostaglandin E receptor Banerjee et al. NM_001126044.1 3 (subtype EP3)2013; Vilella et al. 2013 PTGFR Prostaglandin F receptor Berlanga etNM_000959.3 (FP) al. 2011 PTGS1 Prostaglandin- Aghajanova NM_000962.3endoperoxide synthase 1 et al. 2008; (prostaglandin G/H Sing et al.synthase and 2011; Koot et cyclooxygenase) al. 2012 PTGS2 Prostaglandin-Aghajanova NM_000963.3 endoperoxide synthase 2 et al. 2008;(prostaglandin G/H Sing et al. synthase and 2011; Koot etcyclooxygenase) al. 2012; Banerjee et al. 2013 PTPRZ1 Protein-tyrosineBarnea et al. NM_002851.2 phosphatase, receptor 2012 type, Z polypeptide1 RAC1 Ras-related C3 botulinum Grewal et al., NM_018890.3 toxinsubstrate 1 (rho 2008 family, small GTP binding protein Rac1) RACGAP1Rac GTPase-activating Grewal el al. NM_013277.4 protein 1 2008 RHOA Rashomolog family Heneweer NM_001664.3 member A et al., 2008 RPL13ARibosomal protein L13a V estergaard NM_012423.3 et al. 2011 S100A1 S100calcium binding Díaz-Gimeno NM_006271.1 protein A1 et al. 2011 S100A10S100 calcium binding Dominguez et NM_002966.2 protein A10 al. 2009;Haouzi et al 2009, 2013; Ruíz-Alonso et al. 2013 S100A2 S100 calciumbinding Altmäe et al. NM_005978.3 protein A2 2010 S100P S100 calciumbinding Díaz-Gimeno NM_005980.2 protein P et al. 2011; Zhang et al. 2012SCGB2A2 Secretoglobin, family 2A, Díaz-Gimeno NM_002411.3 member 2 etal. 2011 SCGB3A1 Secretoglobin, family 3A, Altmäe et al. NM_052863.2member 1 2010 SDHA Succinate dehydrogenase Vestergaard NM_004168.3complex, subunit A, et al. 2011; flavoprotein (Fp) Sadek et al. 2012SELL Selectin L Genbaced et NM_000655.4 al. 2003; Aghaj anova et al.2008; Ruíz-Alonso et al. 2012; Banerjee et al. 2013 SERPINA1 Serpinpeptidase Parmar et al. NM_000295.4 inhibitor, clade A (alpha- 2009;Tracey 1 antiproteinase, et al. 2013 antitrypsin), member 1 SERPING1Serpin peptidase Díaz-Gimeno NM_000062.2 inhibitor, clade G (C1 et al.2011; inhibitor), member 1 Ruíz-Alonso et al. 2012 SGK1Serine/glucocorticoid Altmäe et al. NM_005627.3 regulated kinase 1 2010SLPI Secretory leukocyte Díaz-Gimeno NM_003064.3 peptidase inhibitor etal. 2011 SOD2 Superoxide dismutase 2, Díaz-Gimeno NM_000636.3mitochondrial et al. 2011 SPDEF SAM pointed domain Díaz-GimenoNM_012391.2 containing ETS et al. 2011 transcription factor SPP1Secreted phosphoprotein Lessey et al. NM_001251830.1 1 (Osteopontin)2003; Aghajanova et al. 2008; Wei et al. 2009; Díaz- Gimeno et al. 2011;Barnea et al. 2012; Ruíz-Alonso et al. 2012, Garrido- Gómez et al. 2013STAT3 Signal transducer and Catalano et al. NM_139276.2 activator oftranscription 2005 3 (Acute-phase response factor) STC1 Stanniocalcin-1Ruíz-Alonso NM_003155.2 et al. 2012 STMN1 Stathmin 1 Chen et al.NM_001145454.2 2009; Dominguez et al. 2009; Haouzi et al. 2012; Traceyet al. 2013 TAGLN2 Transgelin 2 Dominguez et NM_001277224.1 al. 2009;Haouzi et al 2009, 2013; Díaz-Gimeno et al. 2011 TFF3 Trefoil factor 3Altmäe et al. NM_003226.3 (intestinal) 2010; Ruíz- Alonso et al. 2012TGFB1 Transforming growth Gargiulo et al. NM_000660.6 factor, beta 12004; Aghajanova et al. 2008; Sing et al. 2011; Barnea et al. 2012;Banerjee et al. 2013 TNC Tenascin Barnea et al. NM_002160.3 2012 TNFTumor Necrosis Factor Banerjee et al. NM_000594.3 alpha 2013 TNFRSF11BTumor necrosis factor Barnea et al. NM_002546.3 receptor superfamily,2012 member 11B TSPAN8 Tetraspanin 8 Díaz-Gimeno NM_004616.2 et al. 2011VCAM1 Vascular cell adhesion Díaz-Gimeno NM_001078.3 protein 1 et al.2011; Barnea et al. 2012 VEGFA Vascular Endothelial Banerjee et al.NM_001025366.2 Growth Factor A 2013 WISP2 WNT1-inducible- Altmäe et al.NM_001323370.1 signaling pathway protein 2 2010

Several biological processes mainly related to cellular proliferation,response to wounding, defense and immune response were found to bestatistically over-represented as analyzed by DAVID bioinformatics tool(Table 2).

TABLE 2 GO functional enrichment of the 192 WO1 genes Category TermGenes % p-value BP Regulation of cell proliferation 47 24.6 9.0E−19 BPPositive regulation of cell 33 17.3 1.6E−16 proliferation BP Response towounding 35 18.3 5.1E−15 BP Defense response 36 18.8 6.8E−14 BP Positiveregulation of immune 23 12.0 3.9E−13 system process BP Negativeregulation of transport 18 9.4 1.4E−12 MF Cytokine activity 30 15.73.7E−23 MF Growth factor activity 23 12.0 6.0E−17 MF Cadmium ion binding5 2.6 4.9E−6 MF Antioxidant activity 7 3.7 2.6E−5 CC Extracellularregion part 65 34 6.3E−30 CC Extracellular space 55 28.8 2.0E−28 BP =biological process, MF = molecular function; CC = cellular component

Exploration of the interactions of proteins codified by the selectedgenes rendered the following results: a total of 1,334 protein-proteininteractions when the expected was 425 in the network analysis(clustering coefficient=0.616) (FIG. 1). The set of proteins codified bythe selected genes have more interactions among themselves than whatwould be expected for a random set of proteins of similar size, drawnfrom the genome. Such enrichment indicated that these proteins werebiologically connected as a group.

Expression stability analysis of the eight selected reference genesshowed that Cytochrome C1 (CYC1), glyceraldehyde-3-phosphatedehydrogenase (GAPDH), TATA-box binding protein (TBP) and tyrosine3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta(YWHAZ) were the most stable genes. These genes, previously found to beuseful for normalizing endometrial gene expression data (Vestergaard etal., Mol Hum Reprod 2011; 17:243-254; Sadek et al., Hum Reprod 2012;27:251-256), and were selected and used for normalization of geneexpression values.

Comparison of gene expression data of the selected WOI genes in fertilesubjects on days LH+2 and LH+7 of their cycles showed a total of 85genes presenting significant differences in the fold change (p<0.05;paired t-test) between the proliferative (LH+2) and the secretory phase(LH+7). Most genes were up regulated (n=71) rather than downregulated(n=14) (FIGS. 2A and 2B). Gene ontology (GO) analysis revealed thatthese 85 genes were related to cell division and proliferation, cellsignaling and response, extracellular organization and communication,immunological activity, vascular proliferation, blood pressureregulation and embryo implantation. Additionally, comprehensive analysisof protein-protein interactions showed a total of 23 interactions whenthe expected number was 10 (clustering coefficient=0.218, P=0.000344).

Principal component analysis (PCA) of the 85 genes showing significantfold change between LH+2 and LH+7 revealed that 40 components explainedmore than 99.5% of total sample variance. The variance provided by eachcomponent and the cumulative percentage along the 40 components togetherwith the genes with the highest absolute coefficient value from each ofthe leading principal components are represented in FIG. 3A. These geneswere selected for further discriminant function analysis (DA) (JolliffeAppl Stat 1972; 21:160-173; Jolliffe Applied Stat 1973; 22:21-31). DAassessed the effectiveness of the selected genes to accurately classifythe receptivity status of endometrial biopsies from both fertile donorsand subfertile patients (FIG. 3B).

Within the group of donors, the selected 40 genes disclosed in FIG. 3A(endometrial receptivity panel A genes) allowed accurate classificationof samples into two endometrial receptivity statuses: proliferative(non-receptive) and receptive. Using a DA model based on the 40 genesselected, 100% of LH+2 samples were categorised as non-receptive, andall LH+7 samples were classified as receptive in both the training andtest sets (Table 3).

TABLE 3 Discriminant Functional Analysis Classification ResultsPREDICTED GROUP MEMBERSHIP ORIGINAL (%)^(a,b,c,d) GROUP Non- Pre- Post-MEMBERSHIP N receptive receptive Receptive receptive DONORS Training SetLH + 2 67 100.0 — 0.0 — LH + 7 67 0.0 — 100.0 — Test Set LH + 2 29 100.0— 0.0 — LH + 7 29 0.0 — 100.0 — PATIENTS Training Set Pre-receptive 29 —100.0 0.0 0.0 Receptive 41 — 2.4 95.1 2.4 Post-receptive 13 — 0.0 0.0100.0 Test Set Pre-receptive 13 — 92.3 7.7 0.0 Receptive 18 — 5.6 94.40.0 Post-receptive 6 — 0.0 16.7 83.3 ^(a)Donors training set: 100% oforiginal grouped cases correctly classified ^(b)Donors testing set: 100%of original grouped cases correctly classified ^(c)Patients trainingset: 97.59% of original grouped cases correctly classified ^(d)Patientstesting set: 91.67% of original grouped cases correctly classified

Within the patient group, the endometrial receptivity panel A genesclassification matched the endometrial biopsy status prediction providedby an independent endometrial receptivity test (ERA) in 97.59% samplesin the training set and 91.67% in the testing set. In the training set,two samples were classified differently by the two tests and, in thetesting set, there were three.

The accurate identification of the period of endometrial receptivitycould be key for the achievement of a successful pregnancy in manycouples. The importance of embryonic-endometrial synchrony forsuccessful implantation have been reported in several studies. Shapiroet al. (2008) showed that the lower implantation rates observed in Day 6embryos transferred fresh compared to Day 5 embryos were not due to anembryonic factor but rather to the endometrial moment where embryos weretransferred. No differences in implantation rates were detected incryotransfers of either day 5 or day 6 blastocysts. Similar results werereported by Franasiak et al. (2013) that showed that the diminished ARToutcomes from embryos with delayed blastulation, traditionallyattributed to reduced embryo quality, result from anembryonic-endometrial dissynchrony. These studies highlight theimportance of embryo-endometrial synchrony to increase implantationrates.

Reports exploring the concept of the WOI, show that the timing ofimplantation can also influence pregnancy loss. Wilcox et al. (1999)showed a strong increase in the risk of early pregnancy loss with lateimplantation. Further studies looking at the impact ofendometrial-embryo asynchrony on ART outcomes have found that thecombination of elevated progesterone on the day of trigger (advancedendometrium) and slow growing embryos results in low live birth rates(Healy et al., Hum Reprod 2017; 32:362-367). This problem seems to beinfluenced by maternal age. Shapiro et al. in a recent study (2016)reported elevated incidence of factors associated withembryo-endometrium asynchrony in women over 35 years, high pre-ovulatoryserum progesterone levels and increased numbers of delayed-growthembryos. This, together with the already well known decrease in gametequality of women of advanced reproductive age (Fragouli et al., HumGenet 2013; 132:1001-1013), underlines the importance of women's age forreproductive success and the need for the development of diagnostic andtherapeutic tools to increase the chances of these women becoming amother.

In contrast to previous studies aimed at developing tools forendometrial receptivity evaluation (Horcajadas et al., Fertil Steril2008; 88:S43-S44; Diaz-Gimeno et al., Fertil Steril 2011; 95: 50-60,60-15), a selection of genes was chosen which are involved in biologicalprocesses taking place on the endometrium during the WOI and which arerelated to endometrial preparation for embryonic implantation. Upon theselection performed based on the literature, an over-representation ofprocesses very relevant to the phenomenon of endometrial receptivityacquisition such as cellular proliferation, response to wounding,defense and immune response, were found. Within this group of genes, asubset of 85 especially were found to be interesting as they showedsignificant differences in expression between the proliferative andsecretory phases. These genes GO analyses revealed cellular components,biological processes and molecular functions related to cell signalingand response, extracellular organization, cell division andproliferation, immunological activity, vascular proliferation and embryoimplantation. Interestingly an over-representation of processesinvolving vesicles and exosomes was also found. These terms match withpreviously described processes known to occur at the time ofimplantation. Cellular matrix remodeling and an increase in vascularproliferation permeability and angiogenesis at the implantation site areone of the earliest prerequisites for embryo implantation (Zhang et al.,Mol Reprod Dev 2013; 80:8-21). Also intense communication through cellsignaling between the embryo and the endometrial cells has beendescribed as part of the embryo-endometrial crosstalk essential foradequate embryonic implantation involving, in some cases, extracellularvesicles/exosomes (Ng et al., PLoS One 2013; 8:58502). Also, immuneresponses have been proven to play important roles in early pregnancy(Altmae et al., 2010; and Haller-Kikkatalo et al., Semin Reprod Med2014; 32: 376-384).

PCA analysis, a dimension-reduction tool that can be used to reduce alarge set of variables to a small set that still contains most of theinformation in the large set, revealed that a subset of 40 of the 85genes differentially expressed genes, called endometrial receptivitypanel A genes could accurately differentiate between LH+2 and LH+7.These genes, listed in FIG. 3A, allow 100% correct classification ofendometrial samples from donors into these two status groups. This panelof genes is also able to assess the receptivity status of samples frominfertile patients obtained at the secretory phase, classifying samplesinto: “receptive’, this means the WHO matches the day on which thebiopsy was taken; “pre-receptive”, meaning that the endometrium has notreached its WOI yet or “post-receptive”, i.e., this endometrium hasalready passed its WOI.

Focusing on the technical aspects of the development, high-throughputRT-qPCR was chosen for the analysis of such a panel of endometrialbiopsies. RT-qPCR is the most robust and reliable technique currentlyavailable for gene expression analysis. Alternative methodologies outputsuch as microarray results and RNA-seq expression data need to bevalidated using RT-qPCR methods (Mortazavi et al., Nat Methods 2008;5:621-628; and Costa et al., Transl lung cancer Res 2013; 2:87-91).

The implementation of endometrial receptivity tests such as the onedeveloped in the present study into the clinical practice routine mayhelp guide embryo transfers to be performed in the best endometrialmoment, guaranteeing embryo-endometrial synchrony and thus, allowing forthe achievement of better ART results. Couples with repeatedimplantation failure, previously failed IVF cycles and also couples withrecurrent miscarriage would benefit from the detailed analysis ofendometrial receptivity and embryo-endometrial synchronization. Thisstudy is a new step in the field of personalized medicine in humanreproduction in the management of the endometrium in preparation forembryo transfer, with the final goal of achieving better ART resultsincreasing embryo implantation rate and the likelihood of successfulpregnancies.

OTHER EMBODIMENTS

It is to be understood that while the invention has been described inconjunction with the detailed description thereof, the foregoingdescription is intended to illustrate and not limit the scope of theinvention, which is defined by the scope of the appended claims. Otheraspects, advantages, and modifications are within the scope of thefollowing claims.

What is claimed is:
 1. A method of predicting endometrial receptivitystatus for embryonic implantation in a human subject, the methodcomprising: (a) providing a first biological sample obtained from ahuman subject at a first time point within a menstrual cycle; (b)determining a gene expression profile of a panel of genes in the firstbiological sample, wherein the panel of genes consists of: Annexin A4(ANXA4), Cation channel sperm auxiliary subunit beta (CATSPERB),Prostaglandin F receptor (PTGFR), Prostaglandin-endoperoxide synthase 1(prostaglandin G/H synthase and cyclooxygenase) (PTGS1), Interleukin-8(IL8), Secretoglobin, family 2A, member 2 (SCGB2A2), Angiopoietin-like 1(ANGPTL1), Hypoxanthine phosphoribosyltransferase 1 (HPRT1), Matrixmetallopeptidase 10 (MMP10), Progesterone Receptor (PGR), Integrin alpha8 (ITGA8), Interferon gamma (IFNG), Prokineticin-1 (PROK1), Forkhead boxprotein O1 (FOXO1), C-X-C motif chemokine ligand 1 (CXCL1),Stanniocalcin-1 (STC1), Matrix Metallopeptidase 9 (MMP9), Mucin 1(MUC1), Ribosomal protein L13a (RPL13A), Calcitonin-related polypeptidealpha (CALCA), Integrin subunit alpha-9 (ITGA9), Rac GTPase-activatingprotein 1 (RACGAP1), Glutathione peroxidase 3 (GPX3), Proteinphosphatase 2, regulatory subunit B, gamma (PPP2R2C), Arginase 2 (ARG2),Secretoglobin, family 3A, member 1 (SCGB3A1), Aldehyde dehydrogenasefamily 1 member A3 (ALDH1A3), Apolipoprotein D (APOD), C2calcium-dependent domain-containing protein 4B (C2CD4B), Trefoil factor3 (TFF3), Aquaporin-3 (AQP3), Gap junction protein, alpha 4 (GJA4), RhoGDP-dissociation inhibitor alpha (ARHGDIA), Selectin L (SELL),Apolipoprotein L, 2 (APOL2), Metallothionein-1H (MT1H),Metallothionein-1X (MT1X), Metallothionein-1L (MT1L), Monoamine oxidaseAA (MAOA) and Metallothionein-1F (MT1F) using reverse transcriptionpolymerase chain reaction analysis; and (c) comparing the determinedgene expression profile in step (b) with a gene expression profile ofthe same panel of genes listed in step (b) of a receptive endometrialreceptivity reference group, a non-receptive endometrial receptivityreference group, a pre-receptive endometrial receptivity referencegroup, and a post-receptive endometrial receptivity reference group; (d)identifying the human subject as having: (i) a receptive endometrialstatus, wherein the determined gene expression profile corresponds to agene expression profile of the panel of genes of a receptive endometrialreceptivity reference group, (ii) a non-receptive endometrial status,wherein the determined gene expression profile corresponds to a geneexpression profile of the panel of genes of a non-receptive endometrialreceptivity reference group, (iii) a pre-receptive endometrial status,wherein the determined gene expression profile corresponds to a geneexpression profile of the panel of genes of a pre-receptive endometrialreceptivity reference group, or (iv) a post-receptive endometrialstatus, wherein the determined gene expression profile corresponds to agene expression profile of the panel of genes of a post-receptiveendometrial receptivity reference group; and (e) transferring apre-implantation embryo into the human subject identified as having areceptive endometrial status.
 2. The method of claim 1, wherein thefirst biological sample is an endometrial biopsy obtained from a uterinefundus.
 3. The method of claim 1, wherein the human subject hasundergone assisted reproductive treatment, and the first time point isseven days after a luteinizing hormone surge.
 4. The method of claim 3,wherein the human subject has undergone hormone replacement therapycycles, and the first time point is five days after progesteroneimpregnation.
 5. The method of claim 1, wherein the human subject hasundergone assisted reproductive treatment, and the first time point isseven days after administration of human chorionic gonadotropin (hCG).6. The method of claim 1, further comprising after identifying the humansubject as having a non-receptive endometrial status, a pre-receptiveendometrial status, or a post-receptive endometrial status, (f)obtaining a second biological sample from the human subject at a secondtime point and repeating steps (b), (c), and (d) on the secondbiological sample.
 7. The method of claim 6, further comprising afteridentifying the human subject has having a receptive endometrial status,(g) transferring a pre-implantation embryo into the identified humansubject.
 8. The method of claim 6, wherein the second biological sampleis an endometrial biopsy obtained from a uterine fundus.
 9. The methodof claim 6, wherein the subject is identified as having a post-receptiveendometrial status, and the second biological sample is obtained inanother menstrual cycle one or two days earlier in the another menstrualcycle as compared to when the first biological sample was taken in theprevious menstrual cycle.
 10. The method of claim 6, wherein the subjectis identified as having a pre-receptive endometrial status, and thesecond biological sample is obtained in another menstrual cycle one ortwo days later in the another menstrual cycle as compared to when thefirst biological sample was taken in the previous menstrual cycle. 11.The method of claim 6, wherein the subject is identified as having anon-receptive endometrial status, further comprising instructing ahealthcare professional to select a treatment plan for the identifiedsubject.
 12. The method of claim 6, wherein the subject is identified ashaving a non-receptive endometrial status, further comprising selectinga treatment plan for the identified subject.
 13. The method of claim 12,wherein the treatment plan comprises a hormone replacement therapycycle.
 14. The method of claim 1, wherein the subject has a history ofmiscarriages or stillbirths, and/or a history of fertility issues. 15.The method of claim 1, wherein the subject has had one or more cycles ofin vitro fertilization (IVF).
 16. The method of claim 1, wherein thesubject has previously not had IVF.
 17. The method of claim 1, whereinthe determining step occurs on a chip, an array, a multi-well plate, ora tube.
 18. The method of claim 1, wherein the determining step of eachgene within the panel of genes is performed in a reaction volume of0.005 μL to 100 μL.
 19. The method of claim 1, wherein the determiningstep of each gene within the panel of genes is performed in a reactionvolume of 0.005 μL to 50 μL.
 20. The method of claim 1, wherein thedetermining step is performed using a computer-assisted algorithm. 21.The method of claim 1, wherein the comparing step is performed using aclassification model, wherein the classification model is principalcomponent analysis and/or discriminant functional analysis.
 22. Themethod of claim 1, further comprising modifying the subject's clinicalrecord to identify the subject as having a receptive endometrial status,as having a non-receptive endometrial status, as having a pre-receptiveendometrial status, or as having a post-receptive endometrial status.23. The method of claim 22, wherein the clinical record is stored in acomputer readable medium.